The following relates generally to systems and techniques for identifying altered media data, and more specifically to determining whether media data has been altered based on an immutable ledger.
Examples of media data include video, image, and audio data (which may in some cases include telephonic conversation data). Technology continues to develop for altering media data in ways that are imperceptible to a human consumer (e.g., a human viewer or listener). For example, technology continues to develop for altering image data—even at the pixel level—such that a human viewer of an altered image cannot determine that the image has been altered. Like technology continues to develop for altering other types of media data, such as video and audio data. In general, technologies for altering all types of media data continue to evolve and improve in sophistication, proliferation, ease of use, and lack of detectability.
Improvements in technologies for altering media data give rise, however, to technological problems related to identifying altered media data. Absent technological solutions to such problems, altered media data may be passed off as unaltered media data, or unaltered media data may be plausibly disparaged as altered media data. Thus, technological solutions are desired for identifying altered media data.